等级反应多水平评分者漂移模型的构建

对于评定耗时较长的测验来说,时间因素对评分精确性的影响不容忽视,因此,评分者漂移方面的研究备受关注。研究基于康春花,孙小坚和曾平飞(2016)提出的等级反应多水平侧面模型建构出可用于检测评分者漂移的等级反应多水平评分者漂移模型,并通过模拟研究对模型性能进行验证。结果表明：模型能够精确估计项目和能力参数;且与固定效应模型相比,评分者随机效应模型能更有效地检测出评分者漂移效应,随机效应模型的有效性和稳定性更佳。     

高中会考等值方法的比较研究

本研究采用随机等组设计与铆测验相结合的方案。首先验证了两随机等组的平均数、方差和分布状态无显著差异,再用随机等组的等值分作为等值效标来检验其他等值方法的误差,然后比较了在铆测验设计中三种线性等值方法（在不同总体权重下）的误差值,以选出适合高中合考的等值方法及总体权重。经研究发现：会考等值宜采用Tucker观察分数线性等值方法,并宜选择总体权重W1＝1。     

The Emerging Gender Gap: Cultural and Economic Conservatism in the Netherlands 1970–1992

Research on gender differences in political alignments and cultural orientations in the past decades reveals a large value change in women relative to that in men, indicating that women might recently have become less conservative than men, whereas women used to be more conservative in many respects. In this article this possible reversal in the gender gap in recent decades is analyzed. Recent research has demonstrated that in the Netherlands women are presently less conservative than men. This lower level of conservatism in Dutch women is apparent with respect to both economic and cultural issues. It is investigated whether these gender differences are due to a reversal in the gender gap in the Netherlands and if so, how this emerging gender gap can be explained. Three explanations are hypothesized: one in terms of the characteristics of the youngest generations (the gender-cohort model), the second in terms of growing structural equality between women and men in general (the situational/structural model), and a specification of the second model, in which differential effects of structural factors for women and men are presumed to have their effect (the gender-interaction model). Neither of the three tested models was in itself able to fully explain the results. The gender gap can partly be explained by growing structural equality between women and men, partly by the fact that the gender gap is largest in the youngest generations (economic conservatism), and partly by the fact that the gender gap is largest between groups of "independent" women and their male counterparts. Possible additional determinants are also discussed.     

Optimal scaling of paired comparison and rank order data: An alternative to guttman's formulation

A formulation, which is different from Guttman's is presented. The two formulations are both called the optimal scaling approach, and are proven to provide identical scale values. The proposed formulation has at least two advantages over Guttman's. Namely, (i) the former serves to clarify close relations of the optimal scaling approach to those of Slater and the vector model of preferential choice, and (ii) in addition to the stimulus scale values, it provides scores for the subjects, which indicate the degrees of response consistency (transitivity), relative to the optimum solution. The method is assumption-free and capable of multidimensional analysis.This study was partly supported by the National Research Council Grant (No. A4581) to S. Nishisato. The author is indebted to Dr. Bert F. Green, Jr., Mr. Tomoichi Ishizuka, and anonymous reviewers for their valuable comments on an earlier draft.     

Approximate interval estimation for a certain intraclass correlation coefficient

When the raters participating in a reliability study are a random sample from a larger population of raters, inferences about the intraclass correlation coefficient must be based on the three mean squares from the analysis of variance table summarizing the results: between subjects, between raters, and error. An approximate confidence interval for the parameter is presented as a function of these three mean squares.Dr. Fleiss is also with the Biometrics Research Unit of the New York State Psychiatric Institute. This work was supported in part by grant DE 04068 from the National Institute of Dental Research.     

A lower bound to the probability of choosing the optimal passing score for a mastery test when there is an external criterion

Recently there has been interest in the problem of determining an optimal passing score for a mastery test when the purpose of the test is to predict success or failure on an external criterion. For the case of constant losses for the two error types, a method of determining an optimal passing score is readily derived using standard techniques. The purpose of this note is to describe a lower bound to the probability of identifying an optimal passing score based on a random sample ofN examinees.The work upon which this publication is based was performed pursuant to a grant [contract] with the National Institute of Education, Department of Health, Education and Welfare. Points of view or opinions stated do not necessarily represent official NIE position or policy.     

Paired comparison,triple comparison,and ranking experiments as generalized linear models,and their implementation on GLIM

A wide variety of paired comparison, triple comparison, and ranking experiments may be viewed as generalized linear models. These include paired comparison models based on both the Bradley-Terry and Thurstone-Mosteller approaches, as well as extensions of these models that allow for ties, order of presentation effects, and the presence of covariates. Moreover, the triple comparison model of Pendergrass and Bradley, as well as models for complete rankings of more than three items, can also be represented as generalized linear models. All such models can be easily fit by maximum likelihood, using the widely available GLIM computer package. Additionally, GLIM enables the computation of likelihood ratio statistics for testing many hypotheses of interest. Examples are presented that cover a variety of cases, along with their implementation on GLIM.     

Multilevel SEM with random slopes in discrete data using the pairwise maximum likelihood

Pairwise maximum likelihood (PML) estimation is a promising method for multilevel models with discrete responses. Multilevel models take into account that units within a cluster tend to be more alike than units from different clusters. The pairwise likelihood is then obtained as the product of bivariate likelihoods for all within-cluster pairs of units and items. In this study, we investigate the PML estimation method with computationally intensive multilevel random intercept and random slope structural equation models (SEM) in discrete data. In pursuing this, we first reconsidered the general ‘wide format’ (WF) approach for SEM models and then extend the WF approach with random slopes. In a small simulation study we the determine accuracy and efficiency of the PML estimation method by varying the sample size (250, 500, 1000, 2000), response scales (two-point, four-point), and data-generating model (mediation model with three random slopes, factor model with one and two random slopes). Overall, results show that the PML estimation method is capable of estimating computationally intensive random intercept and random slopes multilevel models in the SEM framework with discrete data and many (six or more) latent variables with satisfactory accuracy and efficiency. However, the condition with 250 clusters combined with a two-point response scale shows more bias.     

An interactive multicriteria decision model for multipurpose reservoir management: the Shellmouth Reservoir

Reservoir management is inherently multicriterial, since any release decision involves implicit trade-offs between various conflicting objectives. The release decision reflects concerns such as flood protection, generation of hydroelectric power, dilution of wastewater and heated effluent, supply of municipal, agricultural and industrial water, maintenance of environmental standards and satisfaction of recreational needs. This paper presents a framework for analysing trade-offs between several decision criteria and includes the dilution of heated effluents from downstream thermoelectric power generation in an optimization model for reservoir management. The model is formulated and analysed in an interactive multicriteria decision-making (MCDM) modelling framework. Rather than providing specific target levels or ad hoc constants in a goal-programming framework as proposed elsewhere, this multicriteria framework suggests a systematic way of evaluating trade-offs by progressive preference assessment. The MCDM model, based on a Chebyshev metric and a contracted cone approach, is learning-oriented and permits a natural exploration of the decision space while maintaining non-dominated decisions. A detailed case study of the Shellmouth Reservoir in Manitoba, Canada serves as an illustration of the model. © 1998 John Wiley & Sons, Ltd.     

Initial excitatory conditioning with the truly random control procedure in rats: The effects of density of the conditioned stimulus

The present experiments were designed to test whether initial excitatory conditioning to a stimulus was obtained, using a within-subject design of the truly random control (TRC) procedure, and to examine the effects of the density of the conditioned stimulus on it. In Experiment 1, the effect of the three levels of CS density (50%, 25%, 20%) was assessed at six different stages of training, using the conditioned suppression of licking in rats. Although all of the groups given the TRC procedure showed evidence of initial excitatory conditioning, it was more marked in the group with the highest CS density than in the other groups. Experiment 2 confirmed the results of Experiment 1, using a between-subject design. The findings are in line with predictions from the Rescorla-Wagner model, and are discussed with reference to other contemporary theories of associative learning.